yeast-GEM: The consensus genome-scale metabolic model of Saccharomyces cerevisiae

Description

This repository contains the current consensus genome-scale metabolic model of Saccharomyces cerevisiae. It is the continuation of the legacy project yeastnet. For the latest release please click here.

Citation

• If you use yeast-GEM please cite the yeast8 paper:

  Lu, H. et al. A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism. Nature Communications 10, 3586 (2019). https://doi.org/10.1038/s41467-019-11581-3.

• Additionally, all yeast-GEM releases are archived in Zenodo, for you to cite the specific version of yeast-GEM that you used in your study, to ensure reproducibility. You should always cite the original publication + the specific version, for instance:

  The yeast consensus genome-scale model [Lu et al. 2019], version 8.3.4 [Sánchez et al. 2019], was used.

  Find the citation details for your specific version here.

Keywords:

Utilisation: experimental data reconstruction; multi-omics integrative analysis; in silico strain design; model template
Field: metabolic-network reconstruction
Type of model: reconstruction; curated
Model source: YeastMetabolicNetwork
Omic source: genomics; metabolomics
Taxonomic name: Saccharomyces cerevisiae
Taxonomy ID: taxonomy:559292
Genome ID: insdc.gca:GCA_000146045.2
Metabolic system: general metabolism
Strain: S288C
Condition: aerobic, glucose-limited, defined media

Model overview

Taxonomy	Template model	Reactions	Metabolites	Genes
Saccharomyces cerevisiae	Yeast 7.6	4058	2742	1150

Last update: 2021-06-24

Installation

Required software - User:

• Matlab user:
  • A functional Matlab installation (MATLAB 7.3 or higher).
  • The COBRA toolbox for MATLAB.
• Python user: Python 3.4, 3.5, 3.6 or 3.7

Required software - Contributor:

• Both of the previous Matlab requirements.
• The RAVEN toolbox for MATLAB.
• A git wrapper added to the search path.

NOTE: You also require git lfs if you wish to run locally any of the following two memote commands:

• memote run
• memote report history

This is because results.db (the database that stores all memote results) is tracked with git lfs.

Dependencies - Recommended Software:

• For Matlab, the libSBML MATLAB API (version 5.17.0 is recommended).
• Gurobi Optimizer for any simulations.

Installation instructions

• For users: Clone it from main in the Github repo, or just download the latest release. If you work in python, please create an environment with all requirements:

  pip install -r requirements/requirements.txt  # installs all dependencies
  touch .env                                    # creates a .env file for locating the root

• For contributors: Fork it to your Github account, and create a new branch from develop.

Usage

Make sure to load/save the model with the corresponding wrapper functions!

• In Matlab:

  cd ./code
  model = loadYeastModel(); % loading
  saveYeastModel(model);    % saving

• In Python:

  import code.io as io
  model = io.read_yeast_model() # loading
  io.write_yeast_model(model)   # saving

Online visualization/simulation

• You can visualize selected pathways of yeast-GEM and perform online constraint-based simulations using Caffeine, by creating a simulation with the latest yeast-GEM version available, and choosing any S. cerevisiae map (currently only iMM904 maps are available). Learn more about Caffeine.
• Additionally, you can interactively navigate model components and visualize 3D representations of all compartments and subsystems of yeast-GEM at Metabolic Atlas. Learn more about Metabolic Atlas.

Contributing

Contributions are always welcome! Please read the contributions guideline to get started.

Contributors

Code contributors are reported automatically by GitHub under Contributors, while other contributions come in as Issues. No newline at end of file